Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide.

Biswapriya Biswavas Misra's insight:

Abstract (provisional)Background

Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide. To design effective breeding strategies that maximize the potential for durable disease resistance it is important to understand the molecular basis of PST pathogenicity. In particular, the characterisation of the structure, function and evolutionary dynamics of secreted effector proteins that are detected by host immune receptors can help guide and prioritize breeding efforts. However, to date, our knowledge of the effector repertoire of cereal rust pathogens is limited.

Results

We re-sequenced genomes of four PST isolates from the US and UK to identify effector candidates and relate them to their distinct virulence profiles. First, we assessed SNP frequencies between all isolates, with heterokaryotic SNPs being over tenfold more frequent (5.29 +/- 2.23 SNPs/kb) than homokaryotic SNPs (0.41 +/- 0.28 SNPs/kb). Next, we implemented a bioinformatics pipeline to integrate genomics, transcriptomics, and effector-focused annotations to identify and classify effector candidates in PST. RNAseq analysis highlighted transcripts encoding secreted proteins that were significantly enriched in haustoria compared to infected tissue. The expression of 22 candidate effector genes was characterised using qRT-PCR, revealing distinct temporal expression patterns during infection in wheat. Lastly, we identified proteins that displayed non-synonymous substitutions specifically between the two UK isolates PST-87/7 and PST-08/21, which differ in virulence to two wheat varieties. By focusing on polymorphic variants enriched in haustoria, we identified five polymorphic effector candidates between PST-87/7 and PST-08/21 among 2,999 secreted proteins. These allelic variants are now a priority for functional validation as virulence/avirulence effectors in the corresponding wheat varieties.

Conclusions

Integration of genomics, transcriptomics, and effector-directed annotation of PST isolates has enabled us to move beyond the single isolate-directed catalogues of effector proteins and develop a framework for mining effector proteins in closely related isolates and relate these back to their defined virulence profiles. This should ultimately lead to more comprehensive understanding of the PST pathogenesis system, an important first step towards developing more effective surveillance and management strategies for one of the most devastating pathogens of wheat.

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platform (mass spectrometry [MS] or nuclear magnetic resonance spectroscopy [NMR]-based) used for data acquisition. Improved machinery in metabolomics generate increasingly complex data sets which create the need for more and better processing and analysis software and in-silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources – in the form of tools, software, and databases - is currently lacking. Thus, here we provide an overview of freely-available, open-source, tools, algorithms and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table.

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platform (mass spectrometry [MS] or nuclear magnetic resonance spectroscopy [NMR]-based) used for data acquisition. Improved machinery in metabolomics generate increasingly complex data sets which create the need for more and better processing and analysis software and in-silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources – in the form of tools, software, and databases - is currently lacking. Thus, here we provide an overview of freely-available, open-source, tools, algorithms and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table.

The assembly of a reference genome sequence of bread wheat is challenging due to its specific features such as the genome size of 17 Gbp, polyploid nature and prevalence of repetitive sequences. BAC-by-BAC sequencing based on chromosomal physical maps, adopted by the International Wheat Genome Sequencing Consortium as the key strategy, reduces problems caused by the genome complexity and polyploidy, but the repeat content still hampers the sequence assembly. Availability of a high-resolution genomic map to guide sequence scaffolding and validate physical map and sequence assemblies would be highly beneficial to obtaining an accurate and complete genome sequence. Here, we chose the short arm of chromosome 7D (7DS) as a model to demonstrate for the first time that it is possible to couple chromosome flow sorting with genome mapping in nanochannel arrays and create a de novo genome map of a wheat chromosome. We constructed a high-resolution chromosome map composed of 371 contigs with an N50 of 1.3 Mb. Long DNA molecules achieved by our approach facilitated chromosome-scale analysis of repetitive sequences and revealed a ~800-kb array of tandem repeats intractable to current DNA sequencing technologies. Anchoring 7DS sequence assemblies obtained by clone-by-clone sequencing to the 7DS genome map provided a valuable tool to improve the BAC-contig physical map and validate sequence assembly on a chromosome-arm scale. Our results indicate that creating genome maps for the whole wheat genome in a chromosome-by-chromosome manner is feasible and that they will be an affordable tool to support the production of improved pseudomolecules.

The impact of nano-scaled materials on photosynthetic organisms needs to be evaluated. Plants represent the largest interface between the environment and biosphere, so understanding how nanoparticles affect them is especially relevant for environmental assessments. Nanotoxicology studies in plants allude to quantum size effects and other properties specific of the nano-stage to explain increased toxicity respect to bulk compounds. However, gene expression profiles after exposure to nanoparticles and other sources of environmental stress have not been compared and the impact on plant defence has not been analysed.

RESULTS:

Arabidopsis plants were exposed to TiO2-nanoparticles, Ag-nanoparticles, and multi-walled carbon nanotubes as well as different sources of biotic (microbial pathogens) or abiotic (saline, drought, or wounding) stresses. Changes in gene expression profiles and plant phenotypic responses were evaluated. Transcriptome analysis shows similarity of expression patterns for all plants exposed to nanoparticles and a low impact on gene expression compared to other stress inducers. Nanoparticle exposure repressed transcriptional responses to microbial pathogens, resulting in increased bacterial colonization during an experimental infection. Inhibition of root hair development and transcriptional patterns characteristic of phosphate starvation response were also observed. The exogenous addition of salicylic acid prevented some nano-specific transcriptional and phenotypic effects, including the reduction in root hair formation and the colonization of distal leaves by bacteria.

CONCLUSIONS:

This study integrates the effect of nanoparticles on gene expression with plant responses to major sources of environmental stress and paves the way to remediate the impact of these potentially damaging compounds through hormonal priming.

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to “rescue” the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

Biswapriya Biswavas Misra's insight:

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to “rescue” the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

A large number of pharmaceuticals, endogenous metabolites, and environmental chemicals act through covalent mechanisms with protein targets. Yet, their specific interactions with the proteome still remain poorly defined for most of these reactive chemicals. Deciphering direct protein targets of reactive small-molecules is critical in understanding their biological action, off-target effects, potential toxicological liabilities, and development of safer and more selective agents. Chemoproteomic technologies have arisen as a powerful strategy that enable the assessment of proteome-wide interactions of these irreversible agents directly in complex biological systems. We review here several chemoproteomic strategies that have facilitated our understanding of specific protein interactions of irreversibly-acting pharmaceuticals, endogenous metabolites, and environmental electrophiles to reveal novel pharmacological, biological, and toxicological mechanisms.

Nitrogen is one of the most essential plant nutrients and one of the major factors limiting crop productivity. Having the goal to perform a more sustainable agriculture, there is a need to maximize biological nitrogen fixation, a feature of legumes. To enhance our understanding of the molecular mechanisms controlling the interaction between legumes and rhizobia, the symbiotic partner fixing and assimilating the atmospheric nitrogen for the plant, researchers took advantage of genetic and genomic resources developed across different legume models (e.g., Medicago truncatula, Lotus japonicus, Glycine max, and Phaseolus vulgaris) to identify key regulatory protein coding genes of the nodulation process. In this study, we are presenting the results of a comprehensive comparative genomic analysis to highlight orthologous and paralogous relationships between the legume genes controlling nodulation. Mining large transcriptomic datasets, we also identified several orthologous and paralogous genes characterized by the induction of their expression during nodulation across legume plant species. This comprehensive study prompts new insights into the evolution of the nodulation process in legume plant and will benefit the scientific community interested in the transfer of functional genomic information between species.

Biswapriya Biswavas Misra's insight:

Nitrogen is one of the most essential plant nutrients and one of the major factors limiting crop productivity. Having the goal to perform a more sustainable agriculture, there is a need to maximize biological nitrogen fixation, a feature of legumes. To enhance our understanding of the molecular mechanisms controlling the interaction between legumes and rhizobia, the symbiotic partner fixing and assimilating the atmospheric nitrogen for the plant, researchers took advantage of genetic and genomic resources developed across different legume models (e.g., Medicago truncatula, Lotus japonicus, Glycine max, and Phaseolus vulgaris) to identify key regulatory protein coding genes of the nodulation process. In this study, we are presenting the results of a comprehensive comparative genomic analysis to highlight orthologous and paralogous relationships between the legume genes controlling nodulation. Mining large transcriptomic datasets, we also identified several orthologous and paralogous genes characterized by the induction of their expression during nodulation across legume plant species. This comprehensive study prompts new insights into the evolution of the nodulation process in legume plant and will benefit the scientific community interested in the transfer of functional genomic information between species.

Bayberry fruits synthesize an extremely thick and unusual layer of crystalline surface wax that accumulates to 30% of fruit dry weight, the highest reported surface lipid accumulation in plants. The composition is also striking, consisting of completely saturated triacylglycerol, diacylglycerol and monoacylglycerol with palmitate and myristate acyl chains. To gain insight into the unique properties of Bayberry wax synthesis we examined the chemical and morphological development of the wax layer, monitored wax biosynthesis through [14C]-radiolabeling, and sequenced the transcriptome. Radiolabeling identified sn-2 MAG as the first glycerolipid intermediate. The kinetics of [14C]-DAG and [14C]-TAG accumulation and the regiospecificity of their [14C]-acyl chains indicated distinct pools of acyl donors and that final TAG assembly occurs outside of cells. The most highly expressed genes were associated with production of cutin, whereas transcripts for conventional TAG synthesis were >50-fold less abundant. The biochemical and expression data together indicate that Bayberry surface glycerolipids are synthesized by a previously unknown pathway for TAG synthesis that is related to cutin biosynthesis. The combination of a unique surface wax and massive accumulation may aid understanding of how plants produce and secrete non-membrane glycerolipids, and also how to engineer alternative pathways for lipid production in non-seeds.

Biswapriya Biswavas Misra's insight:

Bayberry fruits synthesize an extremely thick and unusual layer of crystalline surface wax that accumulates to 30% of fruit dry weight, the highest reported surface lipid accumulation in plants. The composition is also striking, consisting of completely saturated triacylglycerol, diacylglycerol and monoacylglycerol with palmitate and myristate acyl chains. To gain insight into the unique properties of Bayberry wax synthesis we examined the chemical and morphological development of the wax layer, monitored wax biosynthesis through [14C]-radiolabeling, and sequenced the transcriptome. Radiolabeling identified sn-2 MAG as the first glycerolipid intermediate. The kinetics of [14C]-DAG and [14C]-TAG accumulation and the regiospecificity of their [14C]-acyl chains indicated distinct pools of acyl donors and that final TAG assembly occurs outside of cells. The most highly expressed genes were associated with production of cutin, whereas transcripts for conventional TAG synthesis were >50-fold less abundant. The biochemical and expression data together indicate that Bayberry surface glycerolipids are synthesized by a previously unknown pathway for TAG synthesis that is related to cutin biosynthesis. The combination of a unique surface wax and massive accumulation may aid understanding of how plants produce and secrete non-membrane glycerolipids, and also how to engineer alternative pathways for lipid production in non-seeds.

Plants and other multicellular organisms consist of many types of specialized cells. Systems-wide exploration of large scale information from singe cell level is essential to understand how cell works. Root hairs, tubular-shaped outgrowths from root epidermal cells, play important roles in the acquisition of nutrients and water, in the interaction with microbe, and in plant anchorage, and represent an ideal model to study the biology of a single cell type. Single cell sampling combined with omics approaches has been applied to study plant root hairs. This review emphasizes the integration of omics approaches towards understanding the systems biology of root hairs, unraveling the common and plant species-specific properties of root hairs, as well as the concordance of protein and transcript abundance. Understanding plant root hair biology by mining the integrated omics data will provide a way to know how a single cell differentiates, elongates, and functions, which might help molecularly modify crops for developing sustainable agriculture practices.

Whereas de novo assemblies of RNA-Seq data are being published for a growing number of species across the tree of life, there are currently no broadly accepted methods for evaluating such assemblies. Here we present a detailed comparison of 99 transcriptome assemblies, generated with 6 de novo assemblers including CLC, Trinity, SOAP, Oases, ABySS and NextGENe. Controlled analyses of de novo assemblies for Arabidopsis thaliana and Oryza sativa transcriptomes provide new insights into the strengths and limitations of transcriptome assembly strategies. We find that the leading assemblers generate reassuringly accurate assemblies for the majority of transcripts. At the same time, we find a propensity for assemblers to fail to fully assemble highly expressed genes. Surprisingly, the instance of true chimeric assemblies is very low for all assemblers. Normalized libraries are reduced in highly abundant transcripts, but they also lack 1000s of low abundance transcripts. We conclude that the quality of de novo transcriptome assemblies is best assessed through consideration of a combination of metrics: 1) proportion of reads mapping to an assembly 2) recovery of conserved, widely expressed genes, 3) N 50 length statistics, and 4) the total number of unigenes. We provide benchmark Illumina transcriptome data and introduce SCE RNA, a broadly applicable modular protocol for de novo assembly improvement. Finally, our de novo assembly of the Arabidopsis leaf transcriptome revealed ~20 putative Arabidopsis genes lacking in the current annotation.

Biswapriya Biswavas Misra's insight:

Whereas de novo assemblies of RNA-Seq data are being published for a growing number of species across the tree of life, there are currently no broadly accepted methods for evaluating such assemblies. Here we present a detailed comparison of 99 transcriptome assemblies, generated with 6 de novo assemblers including CLC, Trinity, SOAP, Oases, ABySS and NextGENe. Controlled analyses of de novo assemblies for Arabidopsis thaliana and Oryza sativa transcriptomes provide new insights into the strengths and limitations of transcriptome assembly strategies. We find that the leading assemblers generate reassuringly accurate assemblies for the majority of transcripts. At the same time, we find a propensity for assemblers to fail to fully assemble highly expressed genes. Surprisingly, the instance of true chimeric assemblies is very low for all assemblers. Normalized libraries are reduced in highly abundant transcripts, but they also lack 1000s of low abundance transcripts. We conclude that the quality of de novo transcriptome assemblies is best assessed through consideration of a combination of metrics: 1) proportion of reads mapping to an assembly 2) recovery of conserved, widely expressed genes, 3) N50 length statistics, and 4) the total number of unigenes. We provide benchmark Illumina transcriptome data and introduce SCERNA, a broadly applicable modular protocol for de novo assembly improvement. Finally, our de novo assembly of the Arabidopsis leaf transcriptome revealed ~20 putative Arabidopsis genes lacking in the current annotation.

Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum) can be induced by flower removal or leaf deblading, respectively, leading to auxin depletion, which results in increased sensitivity of the abscission zone (AZ) to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq) to obtain the comprehensive transcriptome of tomato flower AZ (FAZ) and leaf AZ (LAZ) during abscission. RNA-Seq was performed on a pool of total RNA extracted from different abscission stages of tomato FAZ and LAZ, followed by de novo assembly. The assembled clusters contained transcripts that are already known in Solanaceae (SOL) genomics database and NCBI databases, and over 8,823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing these novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession.

Biswapriya Biswavas Misra's insight:

Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum) can be induced by flower removal or leaf deblading, respectively, which leads to auxin depletion, resulting in increased sensitivity of the abscission zone (AZ) to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq) to obtain a comprehensive transcriptome of tomato flower AZ (FAZ) and leaf AZ (LAZ) during abscission. RNA-Seq was performed on a pool of total RNA extracted from tomato FAZ and LAZ, at different abscission stages, followed by de novo assembly. The assembled clusters contained transcripts that are already known in the Solanaceae (SOL) genomics and NCBI databases, and over 8823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing the novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession.

The peanut (Arachis hypogaea) is an important food crop in much of the tropical and semi-tropical parts of the world. The peanut is an allotetraploid with an AABB genome formula derived from diploids A. duranensis (A genome) and A. ipaënsis (B genome). The success of an introgression program that aims to improve cultivated varieties of the peanut depends on whether the chosen B genome species is homologous with the B genome of the peanut. While not directly involved in the origin of the peanut to the best of our knowledge, Arachis valida is a B genome species that could potentially be a bridge species or a source of new and different alleles, because of its resistance to diseases and pests. In this study, we investigated the crossability of A. valida with five other B genome species of section Arachis. Eight cross-combinations were made with A. valida and A. gregoryi, A. ipaënsis, A. magna, A. valida, and A. williamsii. Two hundred and forty pollinations were made yielding 61 fruit segments, 61 seeds, one abortion, and 24 hybrid plants. An analysis of the morphological characteristics and pollen viability confirmed that the plants were hybrids. Our results indicated that higher pollen viability of hybrid plants corresponded with higher affinity between parent plants used in crossings. This conclusion corroborates much of previous research carried out by many other authors in the past.

Fungal natural products possess biological activities that are of great value to medicine, agriculture and manufacturing. Recent metagenomic studies accentuate the vastness of fungal taxonomic diversity, and the accompanying specialized metabolic diversity offers a great and still largely untapped resource for natural product discovery. Although fungal natural products show an impressive variation in chemical structures and biological activities, their biosynthetic pathways share a number of key characteristics. First, genes encoding successive steps of a biosynthetic pathway tend to be located adjacently on the chromosome in biosynthetic gene clusters (BGCs). Second, these BGCs are often are located on specific regions of the genome and show a discontinuous distribution among evolutionarily related species and isolates. Third, the same enzyme (super)families are often involved in the production of widely different compounds. Fourth, genes that function in the same pathway are often co-regulated, and therefore co-expressed across various growth conditions. In this mini-review, we describe how these partly interlinked characteristics can be exploited to computationally identify BGCs in fungal genomes and to connect them to their products. Particular attention will be given to novel algorithms to identify unusual classes of BGCs, as well as integrative pan-genomic approaches that use a combination of genomic and metabolomic data for parallelized natural product discovery across multiple strains. Such novel technologies will not only expedite the natural product discovery process, but will also allow the assembly of a high-quality toolbox for the re-design or even de novo design of biosynthetic pathways using synthetic biology approaches.

Drought and salinity are the major factors that limit chickpea production worldwide.

Biswapriya Biswavas Misra's insight:

Drought and salinity are the major factors that limit chickpea production worldwide. We performed whole transcriptome analyses of chickpea genotypes to investigate the molecular basis of drought and salinity stress response/adaptation. Phenotypic analyses confirmed the contrasting responses of the chickpea genotypes to drought or salinity stress. RNA-seq of the roots of drought and salinity related genotypes was carried out under control and stress conditions at vegetative and/or reproductive stages. Comparative analysis of the transcriptomes revealed divergent gene expression in the chickpea genotypes at different developmental stages. We identified a total of 4954 and 5545 genes exclusively regulated in drought-tolerant and salinity-tolerant genotypes, respectively. A significant fraction (~47%) of the transcription factor encoding genes showed differential expression under stress. The key enzymes involved in metabolic pathways, such as carbohydrate metabolism, photosynthesis, lipid metabolism, generation of precursor metabolites/energy, protein modification, redox homeostasis and cell wall component biogenesis, were affected by drought and/or salinity stresses. Interestingly, transcript isoforms showed expression specificity across the chickpea genotypes and/or developmental stages as illustrated by the AP2-EREBP family members. Our findings provide insights into the transcriptome dynamics and components of regulatory network associated with drought and salinity stress responses in chickpea.

The common powdery mildew plant diseases are caused by ascomycete fungi of the order Erysiphales. Their characteristic life style as obligate biotrophs renders functional analyses in these species challenging, mainly because of experimental constraints to genetic manipulation. Global large-scale (“-omics”) approaches are thus particularly valuable and insightful for the characterisation of the life and evolution of powdery mildews. Here we review the knowledge obtained so far from genomic, transcriptomic and proteomic studies in these fungi. We consider current limitations and challenges regarding these surveys and provide an outlook on desired future investigations on the basis of the various –omics technologies

The hyperaccumulating ecotype of Sedum alfredii Hance is a cadmium (Cd)/zinc/lead co-hyperaccumulating species of Crassulaceae. It is a promising phytoremediation candidate accumulating substantial heavy metal ions without obvious signs of poisoning. However, few studies have focused on the regulatory roles of miRNAs and their targets in the hyperaccumulating ecotype of S. alfredii. Here, we combined analyses of the transcriptomics, sRNAs and the degradome to generate a comprehensive resource focused on identifying key regulatory miRNA-target circuits under Cd stress. A total of 87 721 unigenes and 356 miRNAs were identified by deep sequencing, and 79 miRNAs were differentially expressed under Cd stress. Furthermore, 754 target genes of 194 miRNAs were validated by degradome sequencing. A gene ontology (GO) enrichment analysis of differential miRNA targets revealed that auxin, redox-related secondary metabolism and metal transport pathways responded to Cd stress. An integrated analysis uncovered 39 pairs of miRNA targets that displayed negatively correlated expression profiles. Ten miRNA-target pairs also exhibited negative correlations according to a real-time quantitative PCR analysis. Moreover, a coexpression regulatory network was constructed based on profiles of differentially expressed genes. Two hub genes, ARF4 (auxin response factor 4) and AAP3 (amino acid permease 3), which might play central roles in the regulation of Cd-responsive genes, were uncovered. These results suggest that comprehensive analyses of the transcriptomics, sRNAs and the degradome provided a useful platform for investigating Cd hyperaccumulation in S. alfredii, and may provide new insights into the genetic engineering of phytoremediation.

Proceeding to illumina sequencing, determining RNA integrity numbers for poly RNA were separated from each of the four developmental stages of cv. Summer Black leaves by using Illumina HiSeq™ 2000. The sums of 272,941,656 reads were generated from vitis vinifera leaf at four different developmental stages, with more than 27 billion nucleotides of the sequence data. At each growth stage, RNA samples were indexed through unique nucleic acid identifiers and sequenced. KEGG annotation results depicted that the highest number of transcripts in 2,963 (2Avs4A) followed by 1Avs4A (2,920), and 3Avs4A (2,294) out of 15,614 (71%) transcripts were recorded. In comparison, a total of 1,532 transcripts were annotated in GOs, including Cellular component, with the highest number in "Cell part" 251 out of 353 transcripts (71.1%), followed by intracellular organelle 163 out of 353 transcripts (46.2%), while in molecular function and metabolic process 375 out of 525 (71.4%) transcripts, multicellular organism process 40 out of 525 (7.6%) transcripts in biological process were most common in 1Avs2A. While in case of 1Avs3A, cell part 476 out of 662 transcripts (71.9%), and membrane-bounded organelle 263 out of 662 transcripts (39.7%) were recorded in Cellular component. In the grapevine transcriptome, during the initial stages of leaf development 1Avs2A showed single transcript was down-regulated and none of them were up-regulated. While in comparison of 1A to 3A showed one up-regulated (photosystem II reaction center protein C) and one down regulated (conserved gene of unknown function) transcripts, during the hormone regulating pathway namely SAUR-like auxin-responsive protein family having 2 up-regulated and 7 down-regulated transcripts, phytochrome-associated protein showed 1 up-regulated and 9 down-regulated transcripts, whereas genes associated with the Leucine-rich repeat protein kinase family protein showed 7 up-regulated and 1 down-regulated transcript, meanwhile Auxin Resistant 2 has single up-regulated transcript in second developmental stage, although 3 were down-regulated at lateral growth stages (3A and 4A). In the present study, 489 secondary metabolic pathways related genes were identified during leaf growth, which mainly includes alkaloid (40), anthocyanins (21), Diterpenoid (144), Monoterpenoid (90) and Flavonoids (93). Quantitative real-time PCR was applied to validate 10 differentially expressed transcripts patterns from flower, leaf and fruit metabolic pathways at different growth stages.

Plant diseases cause extensive yield loss of crops worldwide, and secretory ‘warfare’ occurs between plants and pathogenic organisms all the time. Filamentous plant pathogens have evolved the ability to manipulate host processes and facilitate colonization through secreting effectors inside plant cells. The stresses from hosts and environment can drive the genome dynamics of plant pathogens. Remarkable advances in plant pathology have been made owing to these adaptable genome regions of several lineages of filamentous phytopathogens. Characterization new effectors and interaction analyses between pathogens and plants have provided molecular insights into the plant pathways perturbed during the infection process. In this mini-review, we highlight promising approaches of identifying novel effectors based on the genome plasticity. We also discuss the interaction mechanisms between plants and their filamentous pathogens and outline the possibilities of effector gene expression under epigenetic control that will be future directions for research.

Highlights A de novo transcriptome reconstruction of olive drupes was performed in two genotypesGene expression was monitored during drupe development in two olive cultivarsTranscripts involved in flavonoid and anthocyanin pathways were analyzed in Cassanese and Leucocarpa cultivarsBoth cultivar and developmental stage impact gene expression in Olea europaea fruits. During ripening, the fruits of the olive tree (Olea europaea L.) undergo a progressive chromatic change characterized by the formation of a red-brown "spot" which gradually extends on the epidermis and in the innermost part of the mesocarp. This event finds an exception in the Leucocarpa cultivar, in which we observe a destabilized equilibrium between the metabolisms of chlorophyll and other pigments, particularly the anthocyanins whose switch-off during maturation promotes the white coloration of fruits. Despite its importance, genomic information on the olive tree is still lacking. Different RNA-seq libraries were generated from drupes of "Leucocarpa" and "Cassanese" olive genotypes, sampled at 100 and 130 days after flowering (DAF), and were used in order to identify transcripts involved in the main phenotypic changes of fruits during maturation and their corresponding expression patterns. A total of 103,359 transcripts were obtained and 3792 and 3064 were differentially expressed in "Leucocarpa" and "Cassanese" genotypes, respectively, during 100-130 DAF transition. Among them flavonoid and anthocyanin related transcripts such as phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavonol 3'-hydrogenase (F3'H), flavonol 3'5 '-hydrogenase (F3'5'H), flavonol synthase (FLS), dihydroflavonol 4-reductase (DFR), anthocyanidin synthase (ANS), UDP-glucose:anthocianidin: flavonoid glucosyltransferase (UFGT) were identified. These results contribute to reducing the current gap in information regarding metabolic processes, including those linked to fruit pigmentation in the olive.

The large amounts of transcriptome data available for Arabidopsis thaliana makes a compelling case for the need to generalize results across studies and extract the most robust and meaningful information possible from them. Various studies seeking to identify water-stress responsive genes only partially overlap in their results. The aim of this work was to combine transcriptomic studies in a systematic way that identifies commonalities in response, taking into account variation among studies due to batch effects as well as sampling variation, while also identifying the effect of study specific variables, such as the method of applying water stress, and the part of the plant mRNA was extracted from. We used meta-analysis, the quantitative synthesis of independent research results, to summarize expression responses to water stress across studies, and meta-regression to model the contribution of covariates that can affect gene expression. We found that some genes with small but consistent differential responses become evident only when results are synthesized across experiments and are missed in individual studies. We also identified genes with expression responses attributable to different plant parts and to alternative methods for inducing water stress. Our results indicate that meta-analysis and meta-regression provide a powerful approach for identifying a robust gene set which is less sensitive to idiosyncratic results and can quantify study characteristics that result in contrasting gene expression responses across studies. Combining meta-analysis with individual analyses can contribute to a richer understanding of the biology of water-stress responses and may prove valuable in other gene expression studies.

The infection of plants by hemibiotrophic pathogens involves a complex and highly regulated transition from an initial biotrophic, asymptomatic stage to a later necrotrophic state, characterized by cell death. Little is known about how this transition is regulated, and there are conflicting views regarding the significance of the plant hormones jasmonic acid (JA) and salicylic acid (SA) in the different phases of infection. To provide a broad view of the hemibiotrophic infection process from the plant perspective, we surveyed the transcriptome of tomato (Solanum lycopersicum) during a compatible interaction with the hemibiotrophic oomycete Phytophthora infestans during three infection stages: biotrophic, the transition from biotrophy to necrotrophy, and the necrotrophic phase. Nearly 10 000 genes corresponding to proteins in approximately 400 biochemical pathways showed differential transcript abundance during the three infection stages, revealing a major reorganization of plant metabolism, including major changes in source–sink relations, as well as secondary metabolites. In addition, more than 100 putative resistance genes and pattern recognition receptor genes were induced, and both JA and SA levels and associated signalling pathways showed dynamic changes during the infection time course. The biotrophic phase was characterized by the induction of many defence systems, which were either insufficient, evaded or suppressed by the pathogen.

Biswapriya Biswavas Misra's insight:

The infection of plants by hemibiotrophic pathogens involves a complex and highly regulated transition from an initial biotrophic, asymptomatic stage to a later necrotrophic state, characterized by cell death. Little is known about how this transition is regulated, and there are conflicting views regarding the significance of the plant hormones jasmonic acid (JA) and salicylic acid (SA) in the different phases of infection. To provide a broad view of the hemibiotrophic infection process from the plant perspective, we surveyed the transcriptome of tomato (Solanum lycopersicum) during a compatible interaction with the hemibiotrophic oomycete Phytophthora infestans during three infection stages: biotrophic, the transition from biotrophy to necrotrophy, and the necrotrophic phase. Nearly 10 000 genes corresponding to proteins in approximately 400 biochemical pathways showed differential transcript abundance during the three infection stages, revealing a major reorganization of plant metabolism, including major changes in source–sink relations, as well as secondary metabolites. In addition, more than 100 putative resistance genes and pattern recognition receptor genes were induced, and both JA and SA levels and associated signalling pathways showed dynamic changes during the infection time course. The biotrophic phase was characterized by the induction of many defence systems, which were either insufficient, evaded or suppressed by the pathogen.

Kentucky bluegrass (Poa pratensis L.) is a prominent turfgrass in the cool-season regions, but it is sensitive to salt stress. Previously, a relatively salt tolerant Kentucky bluegrass accession was identified that maintained green colour under consistent salt applications. In this study, a transcriptome study between the tolerant (PI 372742) accession and a salt susceptible (PI 368233) accession was conducted, under control and salt treatments, and in shoot and root tissues.

RESULTS:

Sample replicates grouped tightly by tissue and treatment, and fewer differentially expressed transcripts were detected in the tolerant PI 372742 samples compared to the susceptible PI 368233 samples, and in root tissues compared to shoot tissues. A de novo assembly resulted in 388,764 transcripts, with 36,587 detected as differentially expressed. Approximately 75 % of transcripts had homology based annotations, with several differences in GO terms enriched between the PI 368233 and PI 372742 samples. Gene expression profiling identified salt-responsive gene families that were consistently down-regulated in PI 372742 and unlikely to contribute to salt tolerance in Kentucky bluegrass. Gene expression profiling also identified sets of transcripts relating to transcription factors, ion and water transport genes, and oxidation-reduction process genes with likely roles in salt tolerance.

CONCLUSIONS:

The transcript assembly represents the first such assembly in the highly polyploidy, facultative apomictic Kentucky bluegrass. The transcripts identified provide genetic information on how this plant responds to and tolerates salt stress in both shoot and root tissues, and can be used for further genetic testing and introgression.

Fungal invasive infections are an increasing health problem. The intrinsic complexity of pathogenic fungi and the unmet clinical need for new and more effective treatments requires a detailed knowledge of the infection process. During infection, fungal pathogens are able to trigger a specific transcriptional program in their host cells. The detailed knowledge of this transcriptional program will allow for a better understanding of the infection process and consequently will help in the future design of more efficient therapeutic strategies. Simultaneous transcriptomic studies of pathogen and host by high-throughput sequencing (dual RNA-seq) is an unbiased protocol to understand the intricate regulatory networks underlying the infectious process. This protocol is starting to be applied to the study of the interactions between fungal pathogens and their hosts. To date, our knowledge of the molecular basis of infection for fungal pathogens is still very limited, and the putative role of regulatory players such as non-coding RNAs or epigenetic factors remains elusive. The wider application of high-throughput transcriptomics in the near future will help to understand the fungal mechanisms for colonization and survival, as well as to characterize the molecular responses of the host cell against a fungal infection.

Biswapriya Biswavas Misra's insight:

Fungal invasive infections are an increasing health problem. The intrinsic complexity of pathogenic fungi and the unmet clinical need for new and more effective treatments requires a detailed knowledge of the infection process. During infection, fungal pathogens are able to trigger a specific transcriptional program in their host cells. The detailed knowledge of this transcriptional program will allow for a better understanding of the infection process and consequently will help in the future design of more efficient therapeutic strategies. Simultaneous transcriptomic studies of pathogen and host by high-throughput sequencing (dual RNA-seq) is an unbiased protocol to understand the intricate regulatory networks underlying the infectious process. This protocol is starting to be applied to the study of the interactions between fungal pathogens and their hosts. To date, our knowledge of the molecular basis of infection for fungal pathogens is still very limited, and the putative role of regulatory players such as non-coding RNAs or epigenetic factors remains elusive. The wider application of high-throughput transcriptomics in the near future will help to understand the fungal mechanisms for colonization and survival, as well as to characterize the molecular responses of the host cell against a fungal infection.

To explore lint fiber initiation-related proteins in allotetraploid cotton (Gossypium hirsutum L.), a comparative proteomic analysis was performed between wild-type cotton (Xu-142) and its fuzzless-lintless mutant (Xu-142-fl) at five developmental time points for lint fiber initiation from -3 to +3 days post-anthesis (dpa). Using two-dimensional gel electrophoresis (2-DE) combined with mass spectrometry (MS) analyses, 91 differentially accumulated protein (DAP) species that are related to fiber initiation were successfully identified, of which 58 preferentially accumulated in the wild-type and 33 species in the fl mutant. These DAPs are involved in various cellular and metabolic processes, mainly including important energy/carbohydrate metabolism, redox homeostasis, amino acid and fatty acid biosynthesis, protein quality control, cytoskeleton dynamics, and anthocyanidin metabolism. Further physiological and biochemical experiments revealed dynamic changes in the carbohydrate flux and H2O2 levels in the cotton fiber initiation process. Compared with those in the fl mutant, the contents of glucose and fructose in wild-type ovules sharply increased after anthesis with a relatively higher rate of amino acid biosynthesis. The relative sugar starvation and lower rate of amino acid biosynthesis in the fl mutant ovules may impede the carbohydrate/energy supply and cell wall synthesis, which is consistent with the proteomic results. However, the H2O2 burst was only observed in the wild-type ovules on the day of anthesis. Cotton boll injection experiments in combination with electron microscope observation collectively indicated that H2O2 burst, which is negatively regulated by ascorbate peroxidases (APx), plays an important role in the fiber initiation process. Taken together, our study demonstrates a putative network of DAP species related to fiber initiation in cotton ovules and provides a foundation for future studies on the specific functions of these proteins in fiber development.

Arsenic is a toxic metalloid known to generate an important oxidative stress in cells. In the present study we focused our attention on an alga related to the genus Coccomyxa, exhibiting an extraordinary capacity to resist high concentrations of arsenite and arsenate. The integrated analysis of high throughput transcriptomic data and non-targeted metabolomic approaches highlighted multiple levels of protection against arsenite. Indeed, Coccomyxa sp. Carn induced a set of transporters potentially preventing the accumulation of this metalloid in the cells and presented a distinct arsenic metabolism in comparison to an other species more sensitive to that compound, i.e. Euglena gracilis, especially in regard to arsenic methylation. Interestingly, Coccomyxa sp. Carn was characterized by a remarkable accumulation of the strong antioxidant glutathione (GSH). Such observation could explain the apparent low oxidative stress in its the intracellular compartment, as suggested by the transcriptomic analysis. In particular, the high amount of GSH in the cell could play an important role for the tolerance to arsenate, as suggested by its partial oxidation into GSSG in presence of this metalloid. Our results therefore reveal that this alga has acquired multiple and original defense mechanisms allowing the colonization of extreme ecosystems such as AMDs.

During ripening, the fruits of the olive tree (Olea europaea L.) undergo a progressive chromatic change characterized by the formation of a red-brown "spot" which gradually extends on the epidermis and in the innermost part of the mesocarp. This event finds an exception in the Leucocarpa cultivar, in which we observe a destabilized equilibrium between the metabolisms of chlorophyll and other pigments, particularly the anthocyanins whose switch-off during maturation promotes the white coloration of fruits. Despite its importance, genomic information on the olive tree is still lacking. Different RNA-seq libraries were generated from drupes of ‘Leucocarpa’ and ‘Cassanese’ olive genotypes, sampled at 100 and 130 days after flowering (DAF), and were used in order to identify transcripts involved in the main phenotypic changes of fruits during maturation and their corresponding expression patterns. A total of 103,359 transcripts were obtained and 3792 and 3064 were differentially expressed in ‘Leucocarpa’ and ‘Cassanese’ genotypes, respectively, during 100-130 DAF transition. Among them flavonoid and anthocyanin related transcripts such as phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavonol 3’-hydrogenase (F3'H), flavonol 3’5’-hydrogenase (F3'5'H), flavonol synthase (FLS), dihydroflavonol 4-reductase (DFR), anthocyanidin synthase (ANS), UDP-glucose:anthocianidin:flavonoid glucosyltransferase (UFGT) were identified. These results contribute to reducing the current gap in information regarding metabolic processes, including those linked to fruit pigmentation in the olive.

Biswapriya Biswavas Misra's insight:

During ripening, the fruits of the olive tree (Olea europaea L.) undergo a progressive chromatic change characterized by the formation of a red-brown “spot” which gradually extends on the epidermis and in the innermost part of the mesocarp. This event finds an exception in the Leucocarpa cultivar, in which we observe a destabilized equilibrium between the metabolisms of chlorophyll and other pigments, particularly the anthocyanins whose switch-off during maturation promotes the white coloration of fruits. Despite its importance, genomic information on the olive tree is still lacking. Different RNA-seq libraries were generated from drupes of “Leucocarpa” and “Cassanese” olive genotypes, sampled at 100 and 130 days after flowering (DAF), and were used in order to identify transcripts involved in the main phenotypic changes of fruits during maturation and their corresponding expression patterns. A total of 103,359 transcripts were obtained and 3792 and 3064 were differentially expressed in “Leucocarpa” and “Cassanese” genotypes, respectively, during 100–130 DAF transition. Among them flavonoid and anthocyanin related transcripts such as phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavonol 3′-hydrogenase (F3′H), flavonol 3′5 ′-hydrogenase (F3′5′H), flavonol synthase (FLS), dihydroflavonol 4-reductase (DFR), anthocyanidin synthase (ANS), UDP-glucose:anthocianidin: flavonoid glucosyltransferase (UFGT) were identified. These results contribute to reducing the current gap in information regarding metabolic processes, including those linked to fruit pigmentation in the olive.

Tea plant (Camellia sinensis) is an economically important beverage crop. Drought stress (DS) seriously limits the growth and development of tea plant, thus affecting crop yield and quality. To elucidate the molecular mechanisms of tea plant responding to DS, we performed transcriptomic analysis of tea plant during the three stages [control (CK) and during DS, and recovery (RC) after DS] using RNA sequencing (RNA-Seq). Totally 378.08 million high-quality trimmed reads were obtained and assembled into 59,674 unigenes, which were extensively annotated. There were 5,955 differentially expressed genes (DEGs) among the three stages. Among them, 3,948 and 1,673 DEGs were up-regulated under DS and RC, respectively. RNA-Seq data were further confirmed by qRT-PCR analysis. Genes involved in abscisic acid (ABA), ethylene, and jasmonic acid biosynthesis and signaling were generally up-regulated under DS and down-regulated during RC. Tea plant potentially used an exchange pathway for biosynthesis of indole-3-acetic acid (IAA) and salicylic acid under DS. IAA signaling was possibly decreased under DS but increased after RC. Genes encoding enzymes involved in cytokinin synthesis were up-regulated under DS, but down-regulated during RC. It seemed probable that cytokinin signaling was slightly enhanced under DS. In total, 762 and 950 protein kinases belonging to 26 families were differentially expressed during DS and RC, respectively. Overall, 547 and 604 transcription factor (TF) genes belonging to 58 families were induced in the DS vs. CK and RC vs. DS libraries, respectively. Most members of the 12 TF families were up-regulated under DS. Under DS, genes related to starch synthesis were down-regulated, while those related to starch decomposition were up-regulated. Mannitol, trehalose and sucrose synthesis-related genes were up-regulated under DS. Proline was probably mainly biosynthesized from glutamate under DS and RC. The mechanism by which ABA regulated stomatal movement under DS and RC was partly clarified. These results document the global and novel responses of tea plant during DS and RC. These data will serve as a valuable resource for drought-tolerance research and will be useful for breeding drought-resistant tea cultivars.

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